The difficulties that we face in finding a cure for cancer are directly related to the heterogeneity within individual neoplasms. A neoplasm is a microcosm of evolution: the differential fitness effects of new mutations lead to selection and subsequent expansion of these cells in the neoplasm. Because evolutionary parameters are critical to understanding how neoplasms develop, progress, and become insensitive to therapy, our objectives are to develop new cell culture models for measuring fitness, and to examine the role of genetic heterogeneity in neoplastic progression and therapeutic resistance. Thus, we will test the following aims: (1) To develop a quantitative method for measuring the fitness effects of specific genetic lesions in Barrett's esophagus allowing us to directly test hypothesized linear models of progression in this system and to determine the fitness effects of newly identified mutations common in progression. To calculate the fitness of specific mutations, we will conduct cell culture competitions between cell lines differing only by the mutation of interest and a fluorescent label. By maintaining the cells in logarithmic growth, we can use the ratio of the growth rates to determine relative fitness. (2) To test the hypothesis that genetic heterogeneity in a neoplasm will fluctuate as selectively advantageous clones expand through the population, and to compare this heterogeneity in different cancer models: cell culture, murine (xenograft, transgenic, and carcinogen-exposure), and human tissue. To measure diversity, fluorescent inter-simple sequence repeat PCR will be performed and fragment lengths analyzed to "fingerprint" particular clones or population of cells. (3) To determine how the application of cancer therapies affects genetic diversity, and how this in turn relates to the development of therapeutic resistance. We will apply chemotherapeutic compounds in a mouse model system and monitor how diversity affects the development of resistance and compare the effect of pulsed vs. continuous therapy and single vs. multiple therapies. This project will develop a novel, simple evolutionary assay for measuring the fitness effect of newly identified cancer lesions, and, for the first time, examine the dynamics of this heterogeneity both in vivo and in vitro. By measuring fitness effects of carcinogenic mutations we will help to define the ordering of mutations during progression that can be used as biomarkers for early detection and risk stratification. Measures of genetic diversity and their relationship to therapeutic resistance can be used for therapeutic prognosis and the development of better pre-clinical models for cancer therapy that will be predictive of clinical results.